Non-Neural Models of Code.
Many non-neural models of code have been proposed over the years [1]}, [2]}, [3]}, [4]}, [5]}, [6]}.
A few of these models condition generation on symbolic information from the context.
Specifically, [6]} use programmatically represented functions to gather information about the context in which productions for program generation are fired, then utilize this information to impose a distribution on rules.
[1]} generate programs using a model that encodes a production's context using a set of “traversal variables.” However, the absence of neural representations in these models puts a ceiling on their performance.
